id stringlengths 3 8 | content stringlengths 100 981k |
|---|---|
1759605 | from __future__ import print_function
import os
import sys
import json
import time
import uuid
import pstool
tcf_stdout = sys.stdout
tcf_stderr = sys.stderr
_GLOBAL_START_TIME = time.time()
_GLOBAL_SOCK = -1
_GLOBAL_STAGE = 0
_GLOBAL_REQUEST_ID = str(uuid.uuid4())
_GLOBAL_FUNCTION_NAME = os.environ.get('SCF_FUNCTION... |
1759615 | import json
from collections import defaultdict
from pathlib import Path
import argparse
from vist_tokenizer import VistTokenizer
def parse_args():
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument('-n', '--name', default='test_results.json', type=str)
parser.add_argument('-l', '-... |
1759670 | from rest_framework import serializers
from testapp.models import RoomBookingText, RoomBookingQ
class RoomBookingTextSerializer(serializers.ModelSerializer):
"""Always fails with ImproperlyConfigured error, because mixin cannot be used with text-based conditions."""
class Meta:
model = RoomBookingTex... |
1759680 | import copy
import torch
import torch_fidelity
import torch.nn.functional as F
from tqdm import tqdm
from .data_utils import get_data_loaders, BigDataset, NoClassDataset, get_datasets
from .log_utils import load_model, load_stats, log, save_images
def normalize(in_channels):
return torch.nn.GroupNorm(num_groups=3... |
1759690 | import pytest
import uvicore
from uvicore.support.dumper import dump
# DB ORM
@pytest.mark.asyncio
async def test_single(app1):
# Single where
from app1.models.post import Post
posts = await Post.query().where('creator_id', 2).get()
assert [3, 4, 5] == [x.id for x in posts]
@pytest.mark.asyncio
asyn... |
1759699 | import json, os, inspect, shutil
from phi.fluidformat import *
class ControlScene:
def __init__(self, path, mode="r", index=None):
self.path = path
self.index = index
if mode.lower() == "r":
with open(os.path.join(path, "description.json"), "r") as file:
self.i... |
1759717 | from django.conf.urls.defaults import *
from django.conf import settings
urlpatterns = patterns('rpg.views',
('^$', 'main'),
('^a/message/new$', 'message_new'),
('^a/room/updates$', 'room_updates'),
('^a/player/new$', 'player_new'),
('^a/player/update_position$', 'player_update_position'),
('^a... |
1759722 | from immudb.grpc import schema_pb2
from pprint import pformat
def py_to_sqlvalue(value):
sqlValue = None
typ = type(value)
if value is None:
sqlValue = schema_pb2.SQLValue(null=True)
elif typ is int:
sqlValue = schema_pb2.SQLValue(n=value)
elif typ is bool:
sqlValue = schem... |
1759733 | import datetime
from mooquant import plotter, strategy
from mooquant.feed import csvfeed
from mooquant.tools import quandl
class MyStrategy(strategy.BacktestingStrategy):
def __init__(self, feed, quandlFeed, instrument):
strategy.BacktestingStrategy.__init__(self, feed)
self.setUseAdjustedValues(... |
1759804 | import numpy as np
import scipy as sp
import scipy.spatial
import scipy.signal
import numexpr as ne
import warnings
import os
from ...misc.basic_functions import rowsum, differentiation_matrix, differentiate
from ...kernels.high_level.laplace import Laplace_Layer_Form, Laplace_Layer_Apply
from ...kernels.high_level.ca... |
1759807 | from downloader import Downloader
cookie = """
ADD YOUR COOKIE HERE
"""
dl = Downloader(cookie=cookie)
# download by class URL:
dl.download_course_by_url('https://www.skillshare.com/classes/Art-Fundamentals-in-One-Hour/189505397')
# or by class ID:
# dl.download_course_by_class_id(189505397)
|
1759809 | import math
import numpy as np
import basis.robot_math as rm
import modeling.mesh_tools as mt
if __name__ == '__main__':
'''
author: weiwei
date: 20201207osaka
'''
mt.convert_to_stl("block.stl", "block.stl", scale_ratio=np.ones(3)*.001) |
1759814 | import keras.backend as K
import numpy as np
from keras.engine.topology import InputSpec, Layer
from keras.layers import (Activation, Concatenate, Conv2D, Flatten, Input,
Reshape)
from keras.models import Model
from nets.mobilenet import mobilenet
def SSD300(input_shape, num_classes... |
1759833 | from django.shortcuts import render
from django.http import HttpResponse
from .models import Student, Log
from django.shortcuts import redirect
import datetime
global stat
stat = ''
# Create your views here.
global selected
selected = None
def index1(request):
logf = []
logs = Log.objects.all()
for log in logs:
... |
1759854 | import _plotly_utils.basevalidators
class MeanlineValidator(_plotly_utils.basevalidators.CompoundValidator):
def __init__(self, plotly_name="meanline", parent_name="violin", **kwargs):
super(MeanlineValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... |
1759877 | import pandas as pd
COUNTRIES = {
"belgium": "B",
"england": "E",
"france": "F",
"germany": "D",
"greece": "G",
"italy": "I",
"portugal": "P",
"scotland": "SC",
"spain": "SP",
"turkey": "T",
}
def list_countries():
"""
Lists all the countries currently available
""... |
1759885 | import pytest
import nltk
nltk.download("wordnet")
from nltk.corpus import wordnet as wn
from lucid.modelzoo.wordnet import (
id_from_synset,
synset_from_id,
imagenet_synset_ids,
imagenet_synsets,
imagenet_synset_from_description,
)
@pytest.fixture()
def synset():
return wn.synset("great_wh... |
1759901 | import unittest
# function spelling mistake is from CodeWars
from katas.beta.binary_pyramid_101 import binary_piramid
class BinaryPyramidTestCase(unittest.TestCase):
def test_equals(self):
self.assertEqual(binary_piramid(1, 4), '1111010')
def test_equals_2(self):
self.assertEqual(binary_pira... |
1759967 | from features.git_commit_features import GitCommitFeatures
from copy import deepcopy
from git_analysis.analyze_git_logs import retrieve_git_logs
from object.features import HistoryFeatures as HistoryFeaturesObj
class HistoryFeatures(GitCommitFeatures):
def __init__(self, rgcm):
super(HistoryFeatures, self... |
1759979 | from setuptools import setup, find_packages
from setuptools.command.install import install
import os
from lyrics import __version__, CONFIG_PATH
this_directory = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(this_directory, 'README.md'), encoding='utf-8') as f:
long_description = f.read()
c... |
1760006 | from os.path import dirname
from pathlib import Path
import pandas as pd
from pandas_datareader import DataReader
from ._utils import fill_and_cut
module_path = Path(dirname(__file__))
def fetch_usstocks(
begin_date="2000-01-01",
end_date="2019-12-31",
n_assets=10,
column="Adj Close",
verbose=T... |
1760007 | from django.apps import AppConfig
class FishingEquipmentConfig(AppConfig):
name = 'lee_fishing.fishing_equipment'
verbose_name = 'Fishing Equipment'
|
1760008 | from prometheus_client.parser import text_string_to_metric_families
for family in text_string_to_metric_families(u"counter_total 1.0\n"):
for sample in family.samples:
print("Name: {0} Labels: {1} Value: {2}".format(*sample))
|
1760036 | import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import math
from functools import partial
import time
__all__ = ['ResNeXt', 'resnet50', 'resnet101']
def conv3x3x3(in_planes, out_planes, stride=1):
# 3x3x3 convolution with padding
return nn.Conv3d(
... |
1760056 | import base64
import os
from pathlib import PurePath
from typing import Union
from django.core.files import File
from esteid.types import PredictableDict
class DataFile:
"""
Interface for file objects that are added to signed containers.
Constructor accepts a path to file (a string or a pathlib *Path) ... |
1760077 | from copy import deepcopy
from multiprocessing import cpu_count
from typing import List, NamedTuple
from mcp.config.dataloader import DataLoaderConfig
from mcp.config.dataloader import parse as parse_dataloader
from mcp.config.dataset import DatasetConfig
from mcp.config.dataset import parse as parse_dataset
from mcp.... |
1760078 | from typing import Any
from typing import Dict
from typing import List
from typing import Tuple
from typing import Union
import numpy as np
import pandas as pd
from sid.config import DTYPE_VIRUS_STRAIN
def prepare_virus_strain_factors(
virus_strains: Dict[str, List[str]], params: pd.DataFrame
) -> Dict[str, Unio... |
1760095 | from typing import List
from topyn.commands import run_command, get_config, get_topyn_excludes
def _extra_args(fix: bool, module: str) -> List[str]:
excludes = "|".join(
[
exclude if exclude[0] != "." else f"\\{exclude}"
for exclude in get_topyn_excludes()
]
)
conf... |
1760134 | from __future__ import print_function
import logging
import os
import random
import numpy as np
from tqdm import tqdm, trange
from transformers_config import *
import torch
from torch.utils.data import DataLoader, RandomSampler
## Optimization
from transformers import (
WEIGHTS_NAME,
AdamW,
get_linear_s... |
1760142 | import pytest
from pathlib import Path
from pythonfmu.csvbuilder import CsvFmuBuilder
EPS = 1e-7
def test_csvslave(tmp_path):
fmpy = pytest.importorskip(
"fmpy", reason="fmpy is not available for testing the produced FMU"
)
csv_file = Path(__file__).parent / "data/csvdemo.csv"
fmu = CsvFmu... |
1760143 | from xmind.tests import logging_configuration as lc
from xmind.core.position import PositionElement
from xmind.tests import base
from unittest.mock import patch
from xmind.core.const import TAG_POSITION, ATTR_X, ATTR_Y
class TestPositionElement(base.Base):
"""Test class for PositionElement class"""
def getLo... |
1760155 | import math
import argparse
import time
from pathlib import Path
from distutils.util import strtobool
import numpy as np
import pandas as pd
pd.set_option("display.max_colwidth", 200)
pd.set_option("display.max_columns", 1000)
pd.set_option("display.width", 1000)
from tqdm import tqdm
from pyquaternion import Quatern... |
1760160 | import random
from smd import config
import numpy as np
def block_mixing_audio(audio1, audio2, overlap=None):
n1 = len(audio1)
n2 = len(audio2)
b1 = int(config.BLOCK_MIXING_MIN * min(n1, n2))
b2 = int(config.BLOCK_MIXING_MAX * min(n1, n2))
if overlap is None:
overlap = random.randint(b1,... |
1760161 | from __future__ import absolute_import
import numpy as np
import itertools
import operator
import random
import sys
import copy
from benchmark.plotting.eval_range_search import compute_AP
from benchmark.sensors.power_capture import power_capture
def compute_recall_without_distance_ties(true_ids, run_ids, count):
... |
1760162 | import asyncio
import pathlib
import aiohttpdemo_polls.db as db
import psycopg2
from faker import Factory
from aiohttpdemo_polls.utils import init_postgres
from sqlalchemy.schema import CreateTable, DropTable
PROJ_ROOT = pathlib.Path(__file__).parent.parent
conf = {"host": "127.0.0.1",
"port": 8080,
... |
1760167 | from .dialogs import (
button_dialog,
checkboxlist_dialog,
input_dialog,
message_dialog,
progress_dialog,
radiolist_dialog,
yes_no_dialog,
)
from .progress_bar import ProgressBar
from .prompt import (
CompleteStyle,
PromptSession,
confirm,
create_confirm_session,
prompt,
... |
1760237 | from torch.utils.data import Dataset
import numpy as np
import io
from PIL import Image
import os
import json
import random
from image_synthesis.utils.misc import instantiate_from_config
def load_img(filepath):
img = Image.open(filepath).convert('RGB')
return img
class CocoDataset(Dataset):
def __init__(s... |
1760262 | from gym.envs.registration import register
register(
id='DartCartPole-v0',
entry_point='gym_dart.envs:DartCartPoleEnv',
)
register(
id='DartParticle-v0',
entry_point='gym_dart.envs:DartParticleEnv',
)
register(
id='DartReacher-v0',
entry_point='gym_dart.envs:DartReacherEnv',
)
|
1760263 | from pandac.PandaModules import *
from direct.interval.IntervalGlobal import *
from direct.particles import ParticleEffect
from direct.particles import Particles
from EffectController import EffectController
from PooledEffect import PooledEffect
from otp.otpbase import OTPRender
from pirates.audio import SoundGlobals
f... |
1760274 | import argparse
from relex.evaluation import semeval2010_task8_evaluation
from relex.evaluation import tacred_evaluation
def _get_parser():
parser = argparse.ArgumentParser(description="Run evaluation")
parser.add_argument(
"--model-dir",
type=str,
required=True,
help="directo... |
1760333 | import concurrent.futures
import urllib.request
import time
def benchmark_url(url):
begin = time.time()
with urllib.request.urlopen(url) as conn:
conn.read()
return (time.time() - begin, url)
class UrlsBenchmarker(object):
def __init__(self, urls):
self._urls = urls
def run(self, ... |
1760364 | import sys
from math import sqrt
import numpy as np
import pandas as pd
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
from sklearn.cross_validation import KFold
from sklearn import ensemble
from sklearn import linear_model as lm
from sklearn.metrics import mean_squared_error as mse
import xgboost as xgb... |
1760430 | import os
import sys
# add project dir to path
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
sys.path.append(BASE_DIR)
from absl import flags
from absl import app
import numpy as np
from pprint import pprint
from meta_learn.util import get_logger
from experiments.util import *
from experiment... |
1760435 | import sys
from typing import List
import math
from delphi.translators.for2py.format import *
from delphi.translators.for2py.arrays import *
from dataclasses import dataclass
from delphi.translators.for2py.types_ext import Float32
import delphi.translators.for2py.math_ext as math
from numbers import Real
def do_while... |
1760466 | import onnx
from onnx import helper
from onnx import AttributeProto, TensorProto, GraphProto, OperatorSetIdProto
from onnx import numpy_helper
import numpy as np
vocab_size=256 #30258
X = helper.make_tensor_value_info('input', TensorProto.FLOAT, ["batch", "seqlen", 128])
unsqueezed_masked_lm_positions = helper.make_t... |
1760484 | class Solution:
def validMountainArray(self, A: List[int]) -> bool:
flag = False
i, n = 1, len(A)
while i < n - 1 and A[i - 1] < A[i] < A[i + 1]:
i += 1
if i < n - 1 and A[i - 1] < A[i] > A[i + 1]:
i += 1
flag = True
while i < n - 1 and A[i... |
1760493 | import json
import os
import time
import rabbitpy
from channelpy.exceptions import ChannelTimeoutException
from codes import BUSY, ERROR, SPAWNER_SETUP, PULLING_IMAGE, CREATING_CONTAINER, UPDATING_STORE, READY, \
REQUESTED, SHUTDOWN_REQUESTED, SHUTTING_DOWN
from config import Config
from docker_utils import Dock... |
1760524 | import logging
import common
import argparse
import uuid
import emission.core.wrapper.user as ecwu
if __name__ == '__main__':
logging.basicConfig(level=logging.DEBUG)
parser = argparse.ArgumentParser(prog="purge_user")
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument("-e",... |
1760533 | import enum
import numpy
import scipy
import time
from AIToolbox import MDP, POMDP
from matplotlib import pyplot as plt
from matplotlib.lines import Line2D
from sklearn.metrics import roc_curve, auc
class Action(enum.Enum):
ANALIZE = 0
BLOCK = 1
PASS = 2
class Observe(enum.Enum):
OK = 0
... |
1760551 | from microbit import display, button_a
import time
NUMBERS = list(range(9, 0, -1))
def countdown():
for i in NUMBERS:
display.show(i)
time.sleep(1)
display.clear()
while True:
if button_a.is_pressed():
countdown()
|
1760563 | import cdutil
import warnings
import vtk
from vtk.util import numpy_support as VN
import vcs
from . import vcs2vtk
import numpy
import math
import os
import traceback
import sys
import cdms2
import cdtime
import inspect
import json
import subprocess
import tempfile
import shutil
from . import VTKAnimate
from . import v... |
1760583 | import cv2, threading, queue
class ThreadingClass:
# initiate threading class
def __init__(self, name):
self.cap = cv2.VideoCapture(name)
# define an empty queue and thread
self.q = queue.Queue()
t = threading.Thread(target=self._reader)
t.daemon = True
t.start()
# read the frames as soon a... |
1760619 | from typing import Generator
import pytest
from sqlalchemy.engine import Engine
from sqlalchemy.orm import sessionmaker, Session
from sqlalchemy.ext.declarative import DeclarativeMeta, declarative_base
@pytest.fixture()
def sa_base() -> DeclarativeMeta:
return declarative_base()
@pytest.fixture()
def session(s... |
1760647 | from django.contrib.gis.geos import Point
from data_importers.management.commands import BaseXpressDemocracyClubCsvImporter
class Command(BaseXpressDemocracyClubCsvImporter):
council_id = "DAL"
addresses_name = "2021-03-19T13:08:53.439791/darlington.gov.uk-1616156390000-.tsv"
stations_name = "2021-03-19T1... |
1760688 | import os
from setuptools import setup, find_packages
import config
setup(
name="scroller",
version=config.version,
author="<NAME>",
author_email="<EMAIL>",
description=config.description,
license="MIT",
py_modules=["scroller", "config"],
keywords="animation utility scrolling text term... |
1760695 | import os
import numpy as np
from .base_data import Dataset, Sequence
from ..utils import read_file
from ..builder import BENCHMARKS
@BENCHMARKS.register_module
class VOT(Dataset):
def __init__(self,
name='vot',
vot_root='data/benchmark/vot17/',
zip_mode=False)... |
1760712 | from KratosDEMApplication import *
from KratosMultiphysics import _ImportApplication
application = KratosDEMApplication()
application_name = "KratosDEMApplication"
_ImportApplication(application, application_name)
|
1760762 | from unittest import TestCase
import numpy as np
from keras_bert.backend import keras
from keras_bert.layers import MaskedGlobalMaxPool1D
class TestPooling(TestCase):
def test_masked_global_max_pool_1d_predict(self):
input_layer = keras.layers.Input(shape=(None,))
embed_layer = keras.layers.Embed... |
1760809 | from setuptools import setup, find_packages
install_requires = [
'torch>=1.9.0',
'torchvision>=0.10.0',
'tqdm'
]
setup(
name='anatome',
version='0.0.3',
description='Ἀνατομή is a PyTorch library to analyze representation of neural networks',
author='<NAME>',
author_email='<EMAIL>',
... |
1760819 | from __future__ import annotations
from typing import List
import numpy as np
from nncg.allocation import Allocation
from nncg.nodes.expressions import Variable
from nncg.nodes.misc import Node
from nncg.writer import Writer
class CHeaderNode(Node):
"""
Class for writing everything in a C file that is above t... |
1760849 | import pdb
import torch
import numpy as np
import torch.optim as optim
class Optimizer(object):
def __init__(self, model, optim_dict):
self.optim_dict = optim_dict
if self.optim_dict["optimizer"] == 'SGD':
self.optimizer = optim.SGD(
model,
lr=self.optim... |
1760887 | from __future__ import print_function
from __future__ import unicode_literals
from __future__ import absolute_import
from __future__ import division
from random import normalvariate
from random import shuffle
from random import uniform
from random import seed
import matplotlib.pyplot as plt
import matplotlib.patches a... |
1760914 | from PyPDF2 import PdfFileWriter, PdfFileReader
import io
import os
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import letter
from reportlab.pdfbase.ttfonts import TTFont
from reportlab.pdfbase import pdfmetrics
from server.utils.misctools import get_pardir
path = get_pardir(os.path.abspath(__file... |
1760935 | import unittest
from reamber.algorithms.generate.sv.generators.svNormalizeBpm import sv_normalize_bpm
from reamber.base.lists.BpmList import BpmList, Bpm
class TestNormalize(unittest.TestCase):
def testNormalize(self):
seq = sv_normalize_bpm(BpmList([Bpm(0, 200), Bpm(100, 50), Bpm(300, 100)]), 100)
... |
1760936 | from discord.ext import commands
import inspect
class source(commands.Cog):
def __init__(self, bot):
self.bot = bot
@commands.command()
async def source(self, ctx, *, command: str):
"""shows source code of a command
Parameters
• command - the name of the command
""... |
1761006 | import sys
sys.path.append('src')
import numpy as np
from objmodel import *
from ParticleGenerator import *
def printUsageInstructions():
print "\n\nUsage: gen_initial_conditions.py filepath static"
print "\tfilepath: the path to a triangulated obj model, whose vertices all lie within a 1.0 width cube centered at ... |
1761048 | import time
from typing import List, Optional
from quarkchain.cluster.shard_db_operator import ShardDbOperator
from quarkchain.core import Address, Log, MinorBlock, MinorBlockHeader
from quarkchain.evm.bloom import bloom
from quarkchain.utils import Logger
class LogFilter:
"""
Filter class for logs, blocks, ... |
1761050 | class Solution:
def sequenceReconstruction(self, org, seqs):
order, orders, graph, seen = collections.defaultdict(int), set(), collections.defaultdict(set), set()
for seq in seqs:
for i in range(len(seq)):
if i > 0:
if seq[i] == seq[i - 1]: return Fals... |
1761062 | from testplan.testing.multitest import testsuite, testcase
# Need to import from project root so that dependency
# is discoverable from interactive code reloader.
from my_tests.dependency import VALUE
@testsuite
class BasicSuite(object):
@testcase(parameters=range(2))
def basic_case(self, env, result, arg):
... |
1761063 | import pytest
from stock_indicators import indicators
class TestAlligator:
def test_standard(self, quotes):
results = indicators.get_alligator(quotes)
# proper quantities
# should always be the same number of results as there is quotes
assert 502 == len(results)
assert 482 ... |
1761080 | import unittest
from setup.settings import *
from numpy.testing import *
import numpy as np
import dolphindb_numpy as dnp
import pandas as pd
import orca
class ArrayAttributesTest(unittest.TestCase):
@classmethod
def setUpClass(cls):
# connect to a DolphinDB server
orca.connect(HOST, PORT, "a... |
1761085 | import torch
import random
from deepspeed.runtime.csr_tensor import CSRTensor
def test_csr_addition_self():
row_count = 10
random.seed(1234)
x = torch.ones(1, 5)
for i in range(row_count - 1):
if random.random() > 0.75:
x = torch.cat([x, torch.ones(1, 5)])
else:
... |
1761091 | import allel
from collections import Counter, OrderedDict
import matplotlib.pyplot as plt
from matplotlib.pyplot import figure
import numpy as np
from operator import itemgetter
import os
import pandas as pd
import random
import sys
from Admixture.utils import *
from Admixture.simulation import simulate
def read_samp... |
1761100 | import logging
import os
import sys
import numpy as np
import argparse
from tempfile import TemporaryDirectory
import matplotlib.pyplot as plt
import matplotlib
# matplotlib.use("TkAgg") # use in pycharm to avoid scientific mode plot?
from tqdm import tqdm
from v2e import desktop
from v2e.emulator import EventEmulato... |
1761148 | import datetime as dt
import os
import sys
import subprocess
from argparse import ArgumentParser
from timeflow import stats as statistics
from timeflow import utils
def log(args):
utils.write_to_log_file(args.message)
def _call_editor(editor, filename):
editor = editor.split()
subprocess.call(editor +... |
1761169 | import fwsynthesizer
from fwsynthesizer.parsers import parse_pf
frontend = fwsynthesizer.Frontend(
name="PF",
diagram="diagrams/pf.diagram",
language_converter=fwsynthesizer.converter(
parser=parse_pf.conf_file.parse_strict,
converter=parse_pf.convert_rules
),
query_configuration=fw... |
1761177 | import glob
import json
import logging
import os
import re
import sys
from datetime import datetime, timezone
from os.path import basename as pbase
from os.path import join as pjoin
from os.path import splitext as psplit
import pytz
import requests
from discord_webhook import DiscordEmbed, DiscordWebhook
"""
A tools ... |
1761255 | from tests.util import match_object_snapshot
from tests.analyzer.util import analyze
input = """
fieldset:
entry = value
entry = value
entry = value
entry = value
entry = value
entry = value
""".strip()
def test_field_analysis():
analysis = analyze(input)
assert match_object_snapshot(... |
1761273 | from .DM import *
class DMConstant(DM):
def __init__(self, constant_size, constant_read, constant_write):
super().__init__()
self.constant_size = constant_size
self.constant_read = constant_read
self.constant_write = constant_write
def disk(self):
return self.constant_size, self.constant_read, self.consta... |
1761284 | SENSOR_IDS = '../METRLA/metr_ids.txt'
DISTANCES = '../METRLA/distances_la_2012.csv'
WEEK = 2
DAY = 1
HOUR = 2 |
1761377 | from unittest.mock import patch
from django.test import TestCase
from ..forms import NewJobForm
from libya_elections.constants import CENTER_ID_LENGTH
class NewJobFormTestCase(TestCase):
def test_simple_case_ok(self):
"""test simple positive case of form submission"""
data = {
'name'... |
1761396 | from django_filters.filterset import FilterSet
from ..search.filter import SearchFilter
from .models import DocumentType, Letter, ReferenceNumber
from .searchset import DocumentTypeSearchSet, LetterSearchSet, ReferenceNumberSearchSet
class DocumentTypeFilterSet(FilterSet):
query = SearchFilter(searchset=Document... |
1761440 | from datetime import datetime
import pytest
from hypothesis import assume, given
from hypothesis_jsonschema import from_schema
from jigu.core.sdk.timestamp import Timestamp
from testtools import assert_serdes_consistent, assert_serdes_exact
@pytest.mark.sdk
class TestTimestampSerdes:
# TODO: write better regex... |
1761451 | import numpy as np
import os
from skimage.io import imread
from skimage.transform import resize
from skimage import color
from cyvlfeat.hog import hog
from non_max_supr_bbox import non_max_supr_bbox
def run_detector(test_scn_path, model, feature_params, threshold=0.5, step_size=3, downsample=0.9):
"""
FUNC: T... |
1761453 | from veripy.parser.syntax import *
from veripy.typecheck.types import *
from veripy.built_ins import FUNCTIONS
from veripy.log import log
def type_check_stmt(sigma : dict, func_sigma : dict, stmt : Stmt):
if isinstance(stmt, Skip):
return sigma
if isinstance(stmt, Seq):
return type_che... |
1761464 | import os
import os.path as osp
from tqdm import tqdm
from pathlib import Path
from collections import defaultdict
import numpy as np
from pyquaternion import Quaternion
from scipy.spatial.transform import Rotation as R
from nuscenes.nuscenes import NuScenes
from nuscenes.utils import splits
from nuscenes.utils.geome... |
1761486 | from rsqueakvm.model.base import W_AbstractObjectWithIdentityHash
from rsqueakvm.model.compiled_methods import (
W_PreSpurCompiledMethod, W_SpurCompiledMethod)
from rsqueakvm.model.pointers import W_PointersObject
from rsqueakvm.primitives.constants import EXTERNAL_CALL
from rsqueakvm.storage_classes import Abstrac... |
1761517 | import FWCore.ParameterSet.Config as cms
from DQMServices.Core.DQMEDHarvester import DQMEDHarvester
segmentTest = DQMEDHarvester("DTSegmentAnalysisTest",
detailedAnalysis = cms.untracked.bool(False),
#Perform basic diagnostic in endLumi/EndRun
... |
1761546 | import ROOT as r
f = r.TFile("tree_cycles_hist.root", "recreate")
t = r.TTree("Events", "")
obj = r.vector("float")()
t.Branch("Jet_pt", obj)
rows = [[], [27.324586868286133, 24.88954734802246, 20.853023529052734], [], [20.330659866333008], [], []]
for i,row in enumerate(rows):
obj.clear()
for x in row:
... |
1761582 | from typing import List, Union
import pandas
from pandas.core.series import Series
from ..model.node_classification_model import NCModel
from ..pipeline.classification_training_pipeline import ClassificationTrainingPipeline
from ..query_runner.query_runner import QueryRunner
class NCTrainingPipeline(ClassificationT... |
1761606 | def count_occurence(list, key):
count = 0
for item in list:
if item == key:
count = count + 1
return count
my_list = [8, 88, -6, 21, 10, 36, 12, 88, 0, 88]
sorted_list = sorted(my_list)
number_of_occurences = count_occurence(sorted_list, 88)
print("88 occurs in " + str(sorted_list) + ":... |
1761631 | from runners.python import Submission
from collections import defaultdict
import pprint
class AyoubSubmission(Submission):
def run(self, s):
lines = s.split('\n')
actions = {}
pause = int(lines[1].split()[5])
for i in range(2, len(lines), 10):
desc = lines[i:i+10]
... |
1761648 | import time
import mxnet as mx
import numpy as np
import mobula
from mobula.testing import assert_almost_equal, gradcheck
import unittest
mobula.op.load('Softmax')
T = np.float32
atol = 2e-3
rtol = 2e-3
def test_softmax1d():
N = 20
data = mx.random.uniform(0, 1, shape=(N, ))
out = mobula.op.Softmax(data... |
1761663 | from ned_base import NEDBase
import re
import os.path
TOPOBATHY_PATTERN = re.compile('^ned19_' \
'([ns])([0-9]{2})x([0257][05])_' \
'([ew])([0-9]{3})x([0257][05])_' \
'[a-z]{2}_[a-z]+_topobathy_20[0-9]{2}.' \
... |
1761673 | import platform
import socket
import struct
from tornado import gen
from microproxy.layer.base import ProxyLayer
class TransparentLayer(ProxyLayer):
SO_ORIGINAL_DST = 80
def __init__(self, context, dest_addr_resolver=None, **kwargs):
super(TransparentLayer, self).__init__(context, **kwargs)
... |
1761695 | from __future__ import print_function
import sys
import numpy as np
def main(argv):
np.random.seed(2)
numPoints = 1001
xs = np.linspace(-5, 5, numPoints)
probs = generateData(numPoints)
convProbs = convolveProbs(probs)
print(np.sum(convProbs))
plt.imshow(convProbs, interpolation = 'none')
plt.sh... |
1761696 | from .abc import ABCLabeler
from .base import BaseLabeler
from .bot import BotLabeler
from .user import UserLabeler
__all__ = ("ABCLabeler", "BaseLabeler", "BotLabeler", "UserLabeler")
|
1761705 | from tests.integration import int_test
example = """
from __future__ import annotations
from typing import List
x: List
"""
expected = """
from __future__ import annotations
x: list
"""
def test_no_duplicate_futures_annotations():
"""
Originally forgot to check for existing futures imports before adding ... |
1761736 | import sys
from kubernetes import watch
# This function returns the kubernetes secret object present in a given namespace
def get_kubernetes_secret(api_instance, namespace, secret_name):
try:
return api_instance.read_namespaced_secret(secret_name, namespace)
except Exception as e:
sys.exit("E... |
1761776 | import argparse
# Parameters
parser = argparse.ArgumentParser(description='Catcher')
parser.add_argument('--grid', dest='grid', type=int, default=11, help='Game grid size.')
parser.add_argument('--hidden', dest='hidden', type=int, default=100, help='Number of neuron in the hidden layer.')
parser.add_argument('--memory... |
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